Cross-Language Pseudo-Relevance Feedback Techniques for Informal Text

Abstract. Previous work has shown that pseudo relevance feedback (PRF) can be effective for cross-lingual information retrieval (CLIR). This research was primarily based on corpora such as news articles that are written using relatively formal language. In this paper, we revisit the problem of CLIR with a focus on the problems that arise with informal text, such as blogs and forums. To address the problem of the two major sources of “noisy ” text, namely translation and the informal nature of the documents, we propose to select between inter- and intra-language PRF, based on the properties of the language of the query and corpora being searched. Experimental results show that this approach can sig-nificantly outperform state-of-the-art results reported for monolingual and cross-lingual environments. Further analysis indicates that inter-language PRF is particularly helpful for queries with poor translation quality. Intra-language PRF is more useful for high-quality translated queries as it reduces the impact of any potential translation errors in documents